class_docstr: Text Processor class implement NER, POS tag, lexical tree parsing.
  EnProcessor is designed by single instance mode.
docstr: Delemmatize function.
  
  This method uses a pre-processed dict which maps (lemma, pos) to
  original token for delemmatizing.
  
  :param tuple|list lemma_and_pos: A tuple or a list of *(lemma, POS)*.
  :return: A word or a list of words, each word represents the specific
      form of input lemma.
docstr_tok: ["Delemmatize","function",".","This","method","uses","a","pre-processed","dict","which","maps","(","lemma",",","pos",")","to","original","token","for","delemmatizing",".",":","param","tuple|list","lemma_and_pos",":","A","tuple","or","a","list","of","*","(","lemma",",","POS",")","*",".",":","return",":","A","word","or","a","list","of","words",",","each","word","represents","the","specific","form","of","input","lemma","."]
code: def get_delemmas(self, lemma_and_pos):
      r"""
      Delemmatize function.
  
      This method uses a pre-processed dict which maps (lemma, pos) to
      original token for delemmatizing.
  
      :param tuple|list lemma_and_pos: A tuple or a list of *(lemma, POS)*.
      :return: A word or a list of words, each word represents the specific
          form of input lemma.
  
      """
      self.check_initialized()
  
      if self.__delemmatize is None:
          self.__delemmatize = self.model_manager.load(
              NLTK_WORDNET_DELEMMA
          )
      if not isinstance(lemma_and_pos, list):
          token, pos = lemma_and_pos
          return (
              self.__delemmatize[token][pos]
              if (token in self.__delemmatize)
              and (pos in self.__delemmatize[token])
              else token
          )
      else:
          return [
              self.__delemmatize[token][pos]
              if (token in self.__delemmatize)
              and (pos in self.__delemmatize[token])
              else token
              for token, pos in lemma_and_pos
          ]
  
imports: import re
  import nltk
  import spacy
  import threading
  from functools import reduce
  from spacy.tokens import Doc
  from .nltk_res_load import *
  from ..settings import *
label_desc: Use image node_id 16 for calling the EnProcessor obj's underlying member method code with example usage: obj.get_delemmas(lemma_and_pos) and returns: unknown, unknown